Results 131 to 140 of about 5,728,670 (281)

Time-series analysis of multidimensional clinical-laboratory data by dynamic Bayesian networks reveals trajectories of COVID-19 outcomes. [PDF]

Comput Methods Programs Biomed, 2022
Longato E, Morieri ML, Sparacino G, Di Camillo B, Cattelan A, Lo Menzo S, Trevenzoli M, Vianello A, Guarnieri G, Lionello F, Avogaro A, Fioretto P, Vettor R, Fadini GP.   +13 more
europepmc   +1 more source

StackingNet: Collective Inference Across Independent AI Foundation Models

Advanced Science, EarlyView.
ABSTRACT Artificial intelligence (AI) built on large foundation models has transformed language understanding, computer vision, and reasoning, yet these systems remain isolated and cannot readily share their capabilities. Coordinating the complementary strengths of independently developed, black‐box foundation models is essential for trustworthy ...
Siyang Li, Chenhao Liu, Dongrui Wu, Zhigang Zeng, Lieyun Ding   +4 more
wiley   +1 more source

A Closed‐Loop Framework for Inverse Design: Dynamic Training and Intelligent Optimization for Heterostructured Materials

Advanced Science, EarlyView.
To accelerate the inverse design of heterostructured metal matrix composites, a closed‐loop scientific machine learning framework integrates continual learning prediction with NSGA‐II‐PMCP optimization. The framework maps microstructural descriptors to strength, toughness, and modulus, expands high‐quality Pareto solutions, and guides experimentally ...
Zhiyan Zhong, Xueru Zheng, Xiao Zhou, Zhengheng Tao, Wan Han, Jingyi Pan, Dian Wu, Ning Gao, Lei Liu, Zhongyang Wang, Fanchao Meng, Tongxiang Fan   +11 more
wiley   +1 more source

Comparative Analysis of Physics-Guided Bayesian Neural Networks for Uncertainty Quantification in Dynamic Systems

Forecasting
Uncertainty quantification (UQ) is critical for modeling complex dynamic systems, ensuring robustness and interpretability. This study extends Physics-Guided Bayesian Neural Networks (PG-BNNs) to enhance model robustness by integrating physical laws into
Xinyue Xu, Julian Wang
doaj   +1 more source

Automation and Active Learning for the Multi‐Objective Optimization of Antibody Formulations

Advanced Science, EarlyView.
Successful antibody formulation necessitates balancing factors such as thermal stability, colloidal stability, and viscosity across a vast excipient design space. This work integrates robotic liquid handling, high‐throughput biophysical characterization, and multi‐objective Bayesian optimization in an iterative closed‐loop Design‐Build‐Test‐Learn cycle.
D. Christopher Radford, Matthew Tamasi, Elena Di Mare, Adam J. Gormley   +3 more
wiley   +1 more source

A Global Methane Observation System to Reduce Uncertainty for Anthropogenic and Natural Sources and Sinks for Detecting and Attributing Climate Feedbacks

Advanced Science, EarlyView.
Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and ...
P. Ciais, S. Peng, J. Chang, F. Li, Q. Zhu, K. Yuan, G. Hugelius, H. Li, Y. Cai, F. Chevallier, K. Tibrewal, E. A. Kort, K. Arndt, J. Watts, B. Buma, N. Besic, P. I. Palmer, H. Cadillo‐Quiroz, E. Euskirchen, M. J. Gondwe, A. Hoyt, R. Jackson, S. Malone, D. Monteverde, S. Natali, M. Ramonet, C. Rey‐Sanchez, L. B. Sagang, E. A. G. Schuur, R. Vargas, R. Varner, Z. Zhang, B. Poulter   +32 more
wiley   +1 more source

Revolutionising Agricultural Sustainability: New ‘Furrow Tillage’ can Mitigate Short‐Term Soil‐to‐Atmosphere CO2 Flux and Promote Soil‐Plant‐Microbe Health

Advanced Science, EarlyView.
Furrow tillage resolves the conventional‐vs.‐no‐tillage trade‐off by simultaneously cutting CO2 efflux to 2.0–3.0 g C m−2 d−1 and unlocking high nutrient availability for the rice rhizosphere. This scalable agronomic solution strengthens soil health, enhances plant physiology, reshapes microbial metabolism, and shifts paddy systems toward a net ...
Arnab Majumdar, Munish Kumar Upadhyay, Argha Ghosh, Rakesh Biswas, Ioly Kotta Loizou, Martin Buck, Mark Tibbett, Biswajit Giri, Debojyoti Moulick, Manoj Kumar Jaiswal, Tarit Roychowdhury   +10 more
wiley   +1 more source

Closing the Empirical Loop: Autonomous AI Agents Conduct End‐to‐end Research With Human Participants

Advanced Science, EarlyView.
A multi‐agent AI system autonomously executes the complete scientific workflow, from hypothesis to manuscript, across three psychological studies involving 288 participants. The system designs experiments, collects real world data, develops analysis pipelines, and writes manuscripts with theoretical rigor comparable to experienced researchers.
Gabrielle Wehr, Reuben Rideaux, Amaya J. Fox, David R. Lightfoot, Jason Tangen, Jason B. Mattingley, Shane E. Ehrhardt   +6 more
wiley   +1 more source

Gaussian copula-based Bayesian Networks for dynamic loads in mooring systems

Applied Ocean Research
Offshore floating structures are experiencing harsh environmental conditions risking their safety. Therefore, mooring lines are crucial for ensuring structures’ stability.
R. Santjer, S. Agarwal, O. Colomés, O. Morales-Nápoles   +3 more
doaj   +1 more source

Cancer‐Associated BCL‐2 Mutants Reveal Mechanisms Towards Venetoclax Resistance

Advanced Science, EarlyView.
Venetoclax (VEN) resistance in chronic lymphocytic leukemia arises from diverse BCL2 mutations. We map mechanisms contributing to VEN resistance across common BCL‐2 variants. G101V and D103Y reduce drug binding and increase sequestration of pro‐apoptotic proteins. V156D blocks VEN allosterically.
Jonas Aufdermauer, Ian de Ridder, Mahjoobeh Ehsani, Marasim Khan, Justin Kale, Lukas P. Frenzel, David Andrews, Spyridoula Karamanou, Ana J. Garcia‐Saez, Geert Bultynck   +9 more
wiley   +1 more source